A new modeling study suggests that tailoring mammography schedules to a woman’s individual 5‑year breast cancer risk may modestly improve outcomes and reduce unnecessary screening harms compared with traditional age‑based recommendations. The analysis, led by Oguzhan Alagoz, PhD, and colleagues and conducted through the Cancer Intervention and Surveillance Modeling Network (CISNET), evaluated 47 risk‑based strategies against standard biennial screening beginning at age 40. Study coauthor Dr. Brian Sprague contributed to the research, which draws on data from the Breast Cancer Surveillance Consortium (including the Vermont Breast Cancer Surveillance System, VBCSS). Access the full manuscript on pubmed.
Using the Breast Cancer Surveillance Consortium risk calculator, researchers simulated outcomes for U.S. women aged 40 and older. Nine of the risk‑stratified strategies produced similar or better reductions in breast cancer mortality while also lowering false‑positive recalls by 8% to 23%.
One example strategy, labeled C4 in the study, adjusted screening timing and frequency based on whether a woman’s risk was low, average, intermediate, or high. This approach was associated with 6% more breast cancer deaths averted and 13% fewer false‑positive results compared with biennial screening for all women aged 40 to 74, as recommended by the U.S. Preventive Services Task Force (USPSTF).
A commentary published alongside the study notes that these findings support a growing interest in precision cancer screening. Experts highlight, however, that several challenges must be addressed before risk‑based mammography can be widely implemented. Current risk calculators remain only moderately accurate for predicting individual risk, and ensuring equitable performance across diverse populations is essential. The commentary also stresses the need for standardized, practical workflows in primary care so clinicians can reassess risk over time and apply screening guidelines consistently.
Despite these hurdles, the authors of both the study and commentary agree that risk‑based screening offers a promising direction, especially as tools such as polygenic risk scores, artificial intelligence–based mammography assessments, and ongoing initiatives like the WISDOM trial continue to advance.
Together, the findings suggest that personalized screening has the potential to improve efficiency, reduce harms, and better support women at both higher and lower risk, moving breast cancer prevention closer to a precision‑medicine model. The full manuscript is available